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Use of the pathfinder network scaling to measure online customer reviews: A theme park study
Author(s) -
Ren Qun,
Xu Feifei,
Ji Xiaowei
Publication year - 2019
Publication title -
strategic change
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.527
H-Index - 16
eISSN - 1099-1697
pISSN - 1086-1718
DOI - 10.1002/jsc.2288
Subject(s) - pathfinder , visitor pattern , theme (computing) , theme park , multidimensional scaling , measure (data warehouse) , similarity (geometry) , computer science , data science , advertising , marketing , world wide web , data mining , geography , artificial intelligence , business , tourism , image (mathematics) , archaeology , machine learning , programming language
We use pathfinder network scaling (PENETS) approach to measure and evaluate theme park visitors' online reviews. PFNETS as an effective tool of big data analytics can be used to identify unobserved meaningful interrelationships between concepts. Although there are many research analyzing online reviews, this study is the first attempt to use an analytical approach of PFNETS to explore online reviews in theme park visitor experiences. The article collects 14,142 effective reviews of the world's first Disneyland in California from TripAdvisor. Using parallel and similarity comparison in pathfinder scaling, four individually but fully connected networks were generated to reveal different visitors' experiences in different segments. The findings indicate the dissimilarity of concept relatedness between different segments and revealed the knowledge gap of marketing to different segments in theme parks.